The prediction for gas chromatographic retention indices of saturated esters on stationary phases of different polarity

A quantitative structure-retention relationship (QSRR) model has been developed for the gas chromatographic Kovلts indices of 98 saturated esters on seven different polar stationary phases by multiple linear regression analysis (MLR). The seven stationary phases are: SE-30, OV-7, DC-710, OV-25, 100% phenyl, DC-230 and DC-530. Chemical descriptors were calculated from the molecular structures by PM3 of Hyperchem 4.0. Principal component analysis (PCA) was applied to extract the data structure. Multiple linear regression was made in forward stepwise manner to select suitable variables in the model. The proposed model had a high multiple square correlation coefficient R2 and low standard error S.E. The result proved the strong predictive power of the model.